# rename columns to a same week+days format <- function (df) {colnames (df) <- colnames (df) %>% gsub ("total_umi_PreL_W0" , "Prevaccine_umi" , .) %>% gsub ("total_umi_fraction_PreL_W0" , "Prevaccine_umi_fraction" , .) %>% gsub ("total_umi_L2_W14" , "Postvaccine_umi" , .) %>% gsub ("total_umi_fraction_L2_W14" , "Postvaccine_umi_fraction" , .) %>% gsub ("total_umi_L3_W22|total_umi_W24" , "Postnivo_umi" , .) %>% gsub ("total_umi_fraction_L3_W22|total_umi_fraction_W24" , "Postnivo_umi_fraction" , .) %>% gsub ("total_umi_w00" , "Prevaccine_umi" , .) %>% gsub ("total_umi_fraction_w00" , "Prevaccine_umi_fraction" , .) %>% gsub ("total_umi_w14" , "Postvaccine_umi" , .) %>% gsub ("total_umi_fraction_w14" , "Postvaccine_umi_fraction" , .) %>% gsub ("total_umi_w22" , "Postnivo_umi" , .) %>% gsub ("total_umi_fraction_w22" , "Postnivo_umi_fraction" , .) %>% gsub ("total_umi_W16" , "w16_umi" , .) %>% gsub ("total_umi_fraction_W16" , "w16_umi_fraction" , .) %>% gsub ("total_umi_LATE_W40" , "w40_umi" , .) %>% gsub ("total_umi_fraction_LATE_W40" , "w40_umi_fraction" , .) %>% gsub ("total_umi_Pre-LL" , "Prevaccine_umi" , .) %>% gsub ("total_umi_fraction_Pre-LL" , "Prevaccine_umi_fraction" , .) %>% gsub ("total_umi_L2" , "Postvaccine_umi" , .) %>% gsub ("total_umi_fraction_L2" , "Postvaccine_umi_fraction" , .) %>% gsub ("total_umi_L3" , "Postnivo_umi" , .) %>% gsub ("total_umi_fraction_L3" , "Postnivo_umi_fraction" , .) return (df)# Calculating LOD <- function (vector) {# Remove zero values before calculating min <- min (vector[vector > 0 ], na.rm = TRUE )# Check if there are no nonzero values if (is.infinite (min_nonzero)) {return (NA )# Calculate LOD return (10 ^ floor (log10 (min_nonzero)))<- function (patient_id, base_path, timepoints, filename) {# subset for specific columns of interest <- function (file_path) {<- read.csv (file_path, sep = " \t " )<- df[,grep ("total|aaSeqCDR3|vGene|jGene|aaImputedVDJSequence" , colnames (df))]$ clonotype_id <- paste (df$ aaSeqCDR3, df$ vGene, df$ jGene, sep= ";" )return (df)# Helper function to select and rename columns <- function (df, suffix) {colnames (df) <- ifelse (colnames (df) != "clonotype_id" ,paste0 (colnames (df), "_" , suffix),colnames (df))<- df[, grep ("total|clonotype_id" , colnames (df))]return (df)# Prepare file paths and suffixes <- lapply (timepoints, function (tp) {<- file.path (base_path, paste0 (filename, patient_id, "_" , tp, ".TRB.tsv" ))<- select_columns (file_path)select_and_rename (df, tp)# Merge all dataframes <- Reduce (function (x, y) merge (x, y, by = "clonotype_id" , all = TRUE ), dataframes)# Replace NA values with 0 is.na (merged_df)] <- 0 <- rename_columns (merged_df)$ Prevaccine_LOD <- calculate_LOD (merged_df$ Prevaccine_umi_fraction)$ Postvaccine_LOD <- calculate_LOD (merged_df$ Postvaccine_umi_fraction)if ("Postnivo_umi_fraction" %in% colnames (merged_df)) { # Fix: Should check for Postnivo_umi_fraction $ Postnivo_LOD <- calculate_LOD (merged_df$ Postnivo_umi_fraction)if ("w40_umi_fraction" %in% colnames (merged_df)) { # Fix: Should check for Postnivo_umi_fraction $ w40_LOD <- calculate_LOD (merged_df$ w40_umi_fraction)if (patient_id == "106" ) { # Fix: Should check for Postnivo_umi_fraction $ w16_LOD <- calculate_LOD (merged_df$ w16_umi_fraction)return (merged_df)<- function (patient_id, base_path, timepoints, filename) {<- function (file_path) {<- read.csv (file_path, sep = " \t " )if (grepl ("PT113" , file_path) & grepl ("w00" , file_path)) {# Removing the first replicate of PT113, had repliacte outlier issue just for this sample. print (file_path)<- df[,grep ("total|aaSeqCDR3|vGene|jGene|aaImputedVDJSequence|uniqueUMICount" , colnames (df))]# Identify columns for replicates 2, 3, and 4 (assuming "total_" is part of the column name) <- grep ("uniqueUMICount" , colnames (df))# Replace the 'total' column with the sum of UMIs from replicates 2, 3, and 4 $ total_umi <- rowSums (df[, umi_columns[2 : 4 ]], na.rm = TRUE )$ total_umi_fraction <- df$ total_umi/ sum (df$ total_umi)<- df[,grep ("total|aaSeqCDR3|vGene|jGene|aaImputedVDJSequence" , colnames (df))]$ clonotype_id <- paste (df$ aaSeqCDR3, df$ vGene, df$ jGene, sep= ";" )return (df)# Helper function to select and rename columns <- function (df, suffix) {colnames (df) <- ifelse (colnames (df) != "clonotype_id" ,paste0 (colnames (df), "_" , suffix),colnames (df))<- df[, grep ("total|clonotype_id" , colnames (df))]return (df)# Prepare file paths and suffixes <- lapply (timepoints, function (tp) {<- file.path (base_path, paste0 (filename, patient_id, tp, ".TRB.tsv" ))<- select_columns (file_path)select_and_rename (df, tp)# Merge all dataframes <- Reduce (function (x, y) merge (x, y, by = "clonotype_id" , all = TRUE ), dataframes)# Replace NA values with 0 is.na (merged_df)] <- 0 <- rename_columns (merged_df)$ Prevaccine_LOD <- calculate_LOD (merged_df$ Prevaccine_umi_fraction)$ Postvaccine_LOD <- calculate_LOD (merged_df$ Postvaccine_umi_fraction)$ Postnivo_LOD <- calculate_LOD (merged_df$ Postvaccine_umi_fraction)return (merged_df)